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Development of NLP-Integrated Intelligent Web System for E-Mental Health.
Hassan, Abid; Ali, M D Iftekhar; Ahammed, Rifat; Bourouis, Sami; Khan, Mohammad Monirujjaman.
  • Hassan A; Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka, 1229, Bangladesh.
  • Ali MDI; Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka, 1229, Bangladesh.
  • Ahammed R; Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka, 1229, Bangladesh.
  • Bourouis S; Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
  • Khan MM; Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka, 1229, Bangladesh.
Comput Math Methods Med ; 2021: 1546343, 2021.
Article in English | MEDLINE | ID: covidwho-1574507
ABSTRACT
As the COVID-19 pandemic continues, the need for a better health care facility is highlighted more than ever. Besides physical health, mental health conditions have become a significant concern. Unfortunately, there are few opportunities for people to receive mental health care. There are inadequate facilities for seeking mental health support even in big cities, let alone remote areas. This paper presents the structure and implementation procedures for a mental health support system combining technology and professionals. The system is a web platform where mental health seekers can register and use functionalities like NLP-based chatbot for personality assessment, chatting with like-minded people, and one-to-one video conferencing with a mental health professional. The video calling feature of the system has emotion detection capabilities using computer vision. The system also includes downloadable prescription facilities and a payment gateway for secure transactions. From a technological aspect, the conversational NLP-based chatbot and computer vision-powered video calling are the system's most important features. The system has a documentation facility to analyze the mental health condition over time. The web platform is built using React.js for the frontend and Express.js for the backend. MongoDB is used as the database of the platform. The NLP chatbot is built on a three-layered deep neural network model that is programmed in the Python language and uses the NLTK, TensorFlow, and Keras sequential API. Video conference is one of the most important features of the platform. To create the video calling feature, Express.js, Socket.io, and Socket.io-client have been used. The emotion detection feature is implemented on video conferences using computer vision, Haar Cascade, and TensorFlow. All the implemented features are tested and work fine. The targeted users for the platform are teenagers, youth, and the middle-aged population. Mental health-seeking is still considered taboo in some societies today. Apart from basic established facilities, this social dilemma of undergoing treatment for mental health is causing severe damage to individuals. A solution to this problem can be a remote platform for mental health support. With this goal in mind, this system is designed to provide mental health support to people remotely from anywhere worldwide.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Software / Mental Health / Telemedicine Limits: Humans Language: English Journal: Comput Math Methods Med Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 2021

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Software / Mental Health / Telemedicine Limits: Humans Language: English Journal: Comput Math Methods Med Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 2021